Clinical Decision Support System

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. faulty data can have serious adverse effects on patient-care decisions. Thus, clinical data often need to be validated. Even good data. not have the basic knowledge necessary to apply them properly. Decision-makers must have broad knowledge of medicine, in-depth familiarity. base still do not guarantee a good decision; good problem-solving skills are equally important. Decision-makers must know how to set.

20.1.1 Types of Decisions By now, you are familiar with the range of clinical decisions. The classic problem of diagnosis (analyzing. when the diagnosis is known, there often are challenging management decisions that test the physician’s knowledge and experience: Should I. diagnosis was incorrect after all? Biomedicine is also replete with decision tasks that do not involve specific patients or their diseases. or the hospital administrator who uses management data to guide decisions about resource allocation in his hospital.

. 2006). Patient data must be adequate to make a valid decision. The problem arises, when the clinician is met with an. amounts of data from various monitors, be aware of the clinical status, patient history, accompanying chronic illnesses, patient’s medication and. interactions, etc. - and on top of that make an appropriate decision about the course of action. The quality of available data. data could have serious adverse effect on patient-care decisions. Knowledge used in decision-making process must be accurate and current. It.

. basic principles of clinical decision support (CDS) systems. CDS systems aim to codify and strategically manage biomedical knowledge to handle challenges in clinical practice using mathematical. and Artificial Intelligence (AI) methods. CDS systems cover a wide range of applications, from diagnosis support to modelling the possibility of occurrence. Diagnosis (CAD) systems can enhance the diagnostic capabilities of physicians and reduce the time required for accurate diagnosis. Modern Therapeutic Decision Support (TDS) systems